A vector-based, multidimensional scanpath similarity measure

Abstract

Figure 1: Are these scanpaths similar? Scanpaths from two participants looking at the same stimulus. AbstractA great need exists in many fields of eye-tracking research for a robust and general method for scanpath comparisons. Current measures either quantize scanpaths in space (string editing measures like the Levenshtein distance) or in time (measures based on attention maps). This paper proposes a new pairwise scanpath similarity measure. Unlike previous measures that either use AOI sequences or forgo temporal order, the new measure defines scanpaths as a series of geometric vectors and compares temporally aligned scanpaths across several dimensions: shape, fixation position, length, direction, and fixation duration. This approach offers more multifaceted insights to how similar two scanpaths are. Eight fictitious scanpath pairs are tested to elucidate the strengths of the new measure, both in itself and compared to two of the currently most popular measures -the Levenshtein distance and attention map correlation.

An evaluation of scanpath-comparison and machine-learning classification algorithms used to study the dynamics of analogy making

“…For all of the scanpathcomparison algorithms, once the dimensionality of the data had been reduced by MDS, the FFBP network was able to correctly classify the left-out participants well above chance, which shows that adults and children do use different strategies to solve analogy problems. As we will show in more detail below, the Jarodzka et al (2010) algorithm produced the best results.…”

“…One of these techniques, developed by Jarodzka, Holmqvist, and Nyström (2010), allows us to answer this question (in the affirmative) significantly better than the other two.…”

“…We will consider three of these techniques: The most widely used is an algorithm developed by Levenshtein (1966), another is the widely used attentional map algorithm (AMAP; Ouerhani, von Wartburg, Hugli, & Muri, 2004;Rajashekar, Van der Linde, Bovik, & Cormack, 2008), and the third is a relatively recent vector-based algorithm developed by Jarodzka, Holmqvist, and Nyström (2010). Each of these algorithms compares two scanpaths and produces a number that indicates how similar they are to each other.…”

“…Vector-based scanpath-comparison (Jarodzka et al, 2010) A novel method of scanpath comparison was recently proposed by Jarodzka et al (2010). This algorithm turns out to be a particularly powerful one for analyzing scanpaths from analogy-making problems.…”

“…We simplified the Jarodzka et al (2010) algorithm by eliminating the relatively complex Dijkstra (1959) treesearch algorithm that it uses. Instead, we simply constructed a path through the difference matrix by moving only rightward, downward, or diagonally from the upperleft cell toward the lower-right cell.…”